Data integration progresses at a different pace at a corporate level, depending on the business units and industry. Industries that are intensive data and information users, e.g., financial services and retail businesses, have processes and methods in place to ensure that information from a central data repository (data warehouse) is made available to different point-of-sale, business support units, and branches.
The availability of information from a data warehouse often occurs as a one-way flow: from the data warehouse to the end-points where information is needed to service customers. The one-way end-point can be a point-of-sale terminal, branches, business support unit's data mart, and the like.
The converse of a one-way movement of data is a two-way movement of data, which is typically not supported by the prior art. Data that flows from a data warehouse to a business support unit, for example, remains locked in the business support unit. All the while, new customer interactions and data are recorded, captured, and stored in local servers without the capability or process in place to bring this enriched data contained in a business support unit back to the data warehouse (the round trip of the data).
Data integration, in the context of call center operations and systems and in accordance with prior art, is typically confined to efforts to bring enterprise-level data to a localized server in a call center in order to create a unified view of a customer relationship for agents who handle calls. This unified view starts as a data extract or as a direct data feed from a central data repository to individual servers or clusters of servers in a call center.
As another example, one-way data flow may occur in banking centers. Typically, banking center system platforms query Systems-of-Records (SOR) via Application Programming Interface (API) or via direct query of stored customer data when a customer is authenticated by a teller. The data flows from the SOR to the teller screen to enable customer servicing. A transaction generates structured data that flow back to the SOR and data warehouse. However, unstructured data, e.g., conversations and images captured, typically do not flow back to the SOR and data warehouse.